14 resultados para Mixed method
em Consorci de Serveis Universitaris de Catalunya (CSUC), Spain
Resumo:
Les lesions per cremades comporten conseqüències a nivell físic, psicològic i social. Les intervencions psicosocials per aquests pacients estan valorades de forma positiva però manquen estudis fets a l’Estat Espanyol. Les intervencions de pacient expert estan donant resultats positius en moltes patologies cròniques però no n’existeix cap per aquest tipus de lesions cròniques. L’objectiu d’aquest estudi és comprendre la utilitat d’una intervenció de pacient expert a pacients d’entre 18 i 30 anys que han patit lesions per cremades recentment. Es realitzaran 9 sessions de pacient expert des de la perspectiva bio-psicosocial. El grup focal serà un grup de 8-10 pacients de 18 a 30 anys amb un mínim del 15% de superfície corporal cremada de grau 2n profund o 3r, residents a Barcelona o rodalies. Les dades s’analitzaran per mètode mixt amb enfocament dominant qualitatiu. La recollida de dades s’obtindrà d’entrevistes, testos i anotacions realitzades prèvia a la primera sessió, al finalitzar les 9 sessions i als 6 mesos de la última sessió. Les limitacions de l’estudi són: el risc de pèrdua dels membres del grup focal a causa del retorn a la vida laboral i l’heterogeneïtat del grup en la fase d’acceptació, principis i valors personals que podrien desviar els resultats.
Resumo:
Background Little is known about the types of ‘sit less, move more’ strategies that appeal to office employees, or what factors influence their use. This study assessed the uptake of strategies in Spanish university office employees engaged in an intervention, and those factors that enabled or limited strategy uptake. Methods The study used a mixed method design. Semi-structured interviews were conducted with academics and administrators (n = 12; 44 ± 12 mean SD age; 6 women) at three points across the five-month intervention, and data used to identify factors that influenced the uptake of strategies. Employees who finished the intervention then completed a survey rating (n = 88; 42 ± 8 mean SD age; 51 women) the extent to which strategies were used [never (1) to usually (4)]; additional survey items (generated from interviewee data) rated the impact of factors that enabled or limited strategy uptake [no influence (1) to very strong influence (4)]. Survey score distributions and averages were calculated and findings triangulated with interview data. Results Relative to baseline, 67% of the sample increased step counts post intervention (n = 59); 60% decreased occupational sitting (n = 53). ‘Active work tasks’ and ‘increases in walking intensity’ were the strategies most frequently used by employees (89% and 94% sometimes or usually utilised these strategies); ‘walk-talk meetings’ and ‘lunchtime walking groups’ were the least used (80% and 96% hardly ever or never utilised these strategies). ‘Sitting time and step count logging’ was the most important enabler of behaviour change (mean survey score of 3.1 ± 0.8); interviewees highlighted the motivational value of being able to view logged data through visual graphics in a dedicated website, and gain feedback on progress against set goals. ‘Screen based work’ (mean survey score of 3.2 ± 0.8) was the most significant barrier limiting the uptake of strategies. Inherent time pressures and cultural norms that dictated sedentary work practices limited the adoption of ‘walk-talk meetings’ and ‘lunch time walking groups’. Conclusions The findings provide practical insights into which strategies and influences practitioners need to target to maximise the impact of ‘sit less, move more’ occupational intervention strategies.
Resumo:
Digital learner portfolios are of growing importance in higher education as the sector seeks new teaching-learning-assessment methods which promote students" autonomy as managers of their own virtual learning environment. The purpose of this study was to analyse descriptively the undergraduate students" perceptions, attitudes and behaviour when using an eportfolio to support their learning and assessment in practice based courses at two traditional Spanish universities. The participants were 88 students, who were studying through a blended learning mode. Data were collected through questionnaires: a computer experience survey, another which examined the psychological, pedagogical and technological dimensions of eportfolios use. Further, an individual overall reflection was obtained from each student to help gain an understanding of their experiences of using the eportfolio. A mixed-method analysis was applied in order to study the impact of this technological innovation on students and their satisfaction. The results showed that the students had positive opinions and self-efficiency through the eportfolio as a tool to manage their learning and assessment during a semester, especially from the second month of use. However, the expected impact on their learning was not so significant. Nevertheless, the students emphasised that the eportfolio was valuable as a personal developmental learning tool.
Resumo:
We propose a mixed finite element method for a class of nonlinear diffusion equations, which is based on their interpretation as gradient flows in optimal transportation metrics. We introduce an appropriate linearization of the optimal transport problem, which leads to a mixed symmetric formulation. This formulation preserves the maximum principle in case of the semi-discrete scheme as well as the fully discrete scheme for a certain class of problems. In addition solutions of the mixed formulation maintain exponential convergence in the relative entropy towards the steady state in case of a nonlinear Fokker-Planck equation with uniformly convex potential. We demonstrate the behavior of the proposed scheme with 2D simulations of the porous medium equations and blow-up questions in the Patlak-Keller-Segel model.
Resumo:
We study preconditioning techniques for discontinuous Galerkin discretizations of isotropic linear elasticity problems in primal (displacement) formulation. We propose subspace correction methods based on a splitting of the vector valued piecewise linear discontinuous finite element space, that are optimal with respect to the mesh size and the Lamé parameters. The pure displacement, the mixed and the traction free problems are discussed in detail. We present a convergence analysis of the proposed preconditioners and include numerical examples that validate the theory and assess the performance of the preconditioners.
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The problem of stability analysis for a class of neutral systems with mixed time-varying neutral, discrete and distributed delays and nonlinear parameter perturbations is addressed. By introducing a novel Lyapunov-Krasovskii functional and combining the descriptor model transformation, the Leibniz-Newton formula, some free-weighting matrices, and a suitable change of variables, new sufficient conditions are established for the stability of the considered system, which are neutral-delay-dependent, discrete-delay-range dependent, and distributeddelay-dependent. The conditions are presented in terms of linear matrix inequalities (LMIs) and can be efficiently solved using convex programming techniques. Two numerical examples are given to illustrate the efficiency of the proposed method
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This paper studies the rate of convergence of an appropriatediscretization scheme of the solution of the Mc Kean-Vlasovequation introduced by Bossy and Talay. More specifically,we consider approximations of the distribution and of thedensity of the solution of the stochastic differentialequation associated to the Mc Kean - Vlasov equation. Thescheme adopted here is a mixed one: Euler/weakly interactingparticle system. If $n$ is the number of weakly interactingparticles and $h$ is the uniform step in the timediscretization, we prove that the rate of convergence of thedistribution functions of the approximating sequence in the $L^1(\Omega\times \Bbb R)$ norm and in the sup norm is of theorder of $\frac 1{\sqrt n} + h $, while for the densities is ofthe order $ h +\frac 1 {\sqrt {nh}}$. This result is obtainedby carefully employing techniques of Malliavin Calculus.
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This paper aims to estimate a translog stochastic frontier production function in the analysis of a panel of 150 mixed Catalan farms in the period 1989-1993, in order to attempt to measure and explain variation in technical inefficiency scores with a one-stage approach. The model uses gross value added as the output aggregate measure. Total employment, fixed capital, current assets, specific costs and overhead costs are introduced into the model as inputs. Stochasticfrontier estimates are compared with those obtained using a linear programming method using a two-stage approach. The specification of the translog stochastic frontier model appears as an appropriate representation of the data, technical change was rejected and the technical inefficiency effects were statistically significant. The mean technical efficiency in the period analyzed was estimated to be 64.0%. Farm inefficiency levels were found significantly at 5%level and positively correlated with the number of economic size units.
Resumo:
Spatial resolution is a key parameter of all remote sensing satellites and platforms. The nominal spatial resolution of satellites is a well-known characteristic because it is directly related to the area in ground that represents a pixel in the detector. Nevertheless, in practice, the actual resolution of a specific image obtained from a satellite is difficult to know precisely because it depends on many other factors such as atmospheric conditions. However, if one has two or more images of the same region, it is possible to compare their relative resolutions. In this paper, a wavelet-decomposition-based method for the determination of the relative resolution between two remotely sensed images of the same area is proposed. The method can be applied to panchromatic, multispectral, and mixed (one panchromatic and one multispectral) images. As an example, the method was applied to compute the relative resolution between SPOT-3, Landsat-5, and Landsat-7 panchromatic and multispectral images taken under similar as well as under very different conditions. On the other hand, if the true absolute resolution of one of the images of the pair is known, the resolution of the other can be computed. Thus, in the last part of this paper, a spatial calibrator that is designed and constructed to help compute the absolute resolution of a single remotely sensed image is described, and an example of its use is presented.
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In this paper we describe the results of a simulation study performed to elucidate the robustness of the Lindstrom and Bates (1990) approximation method under non-normality of the residuals, under different situations. Concerning the fixed effects, the observed coverage probabilities and the true bias and mean square error values, show that some aspects of this inferential approach are not completely reliable. When the true distribution of the residuals is asymmetrical, the true coverage is markedly lower than the nominal one. The best results are obtained for the skew normal distribution, and not for the normal distribution. On the other hand, the results are partially reversed concerning the random effects. Soybean genotypes data are used to illustrate the methods and to motivate the simulation scenarios
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In this paper we analyse, using Monte Carlo simulation, the possible consequences of incorrect assumptions on the true structure of the random effects covariance matrix and the true correlation pattern of residuals, over the performance of an estimation method for nonlinear mixed models. The procedure under study is the well known linearization method due to Lindstrom and Bates (1990), implemented in the nlme library of S-Plus and R. Its performance is studied in terms of bias, mean square error (MSE), and true coverage of the associated asymptotic confidence intervals. Ignoring other criteria like the convenience of avoiding over parameterised models, it seems worst to erroneously assume some structure than do not assume any structure when this would be adequate.
Resumo:
Background: MLPA method is a potentially useful semi-quantitative method to detect copy number alterations in targeted regions. In this paper, we propose a method for the normalization procedure based on a non-linear mixed-model, as well as a new approach for determining the statistical significance of altered probes based on linear mixed-model. This method establishes a threshold by using different tolerance intervals that accommodates the specific random error variability observed in each test sample.Results: Through simulation studies we have shown that our proposed method outperforms two existing methods that are based on simple threshold rules or iterative regression. We have illustrated the method using a controlled MLPA assay in which targeted regions are variable in copy number in individuals suffering from different disorders such as Prader-Willi, DiGeorge or Autism showing the best performace.Conclusion: Using the proposed mixed-model, we are able to determine thresholds to decide whether a region is altered. These threholds are specific for each individual, incorporating experimental variability, resulting in improved sensitivity and specificity as the examples with real data have revealed.
Resumo:
Background: Optimization methods allow designing changes in a system so that specific goals are attained. These techniques are fundamental for metabolic engineering. However, they are not directly applicable for investigating the evolution of metabolic adaptation to environmental changes. Although biological systems have evolved by natural selection and result in well-adapted systems, we can hardly expect that actual metabolic processes are at the theoretical optimum that could result from an optimization analysis. More likely, natural systems are to be found in a feasible region compatible with global physiological requirements. Results: We first present a new method for globally optimizing nonlinear models of metabolic pathways that are based on the Generalized Mass Action (GMA) representation. The optimization task is posed as a nonconvex nonlinear programming (NLP) problem that is solved by an outer- approximation algorithm. This method relies on solving iteratively reduced NLP slave subproblems and mixed-integer linear programming (MILP) master problems that provide valid upper and lower bounds, respectively, on the global solution to the original NLP. The capabilities of this method are illustrated through its application to the anaerobic fermentation pathway in Saccharomyces cerevisiae. We next introduce a method to identify the feasibility parametric regions that allow a system to meet a set of physiological constraints that can be represented in mathematical terms through algebraic equations. This technique is based on applying the outer-approximation based algorithm iteratively over a reduced search space in order to identify regions that contain feasible solutions to the problem and discard others in which no feasible solution exists. As an example, we characterize the feasible enzyme activity changes that are compatible with an appropriate adaptive response of yeast Saccharomyces cerevisiae to heat shock Conclusion: Our results show the utility of the suggested approach for investigating the evolution of adaptive responses to environmental changes. The proposed method can be used in other important applications such as the evaluation of parameter changes that are compatible with health and disease states.
Resumo:
BACKGROUND: Over the last 20 years, a number of instruments developed for the assessment of health-related quality of life (HRQL) in dementia have been introduced. The aim of this review is to synthesize evidence from published reviews on HRQL measures in dementia and any new literature in order to identify dementia specific HRQL instruments, the domains they measure, and their operationalization. METHODS: An electronic search of PsycINFO and PubMed was conducted, from inception to December 2011 using a combination of key words that included quality of life and dementia. RESULTS: Fifteen dementia-specific HRQL instruments were identified. Instruments varied depending on their country of development/validation, dementia severity, data collection method, operationalization of HRQL in dementia, psychometric properties, and the scoring. The most common domains assessed include mood, self-esteem, social interaction, and enjoyment of activities. CONCLUSIONS: A number of HRQL instruments for dementia are available. The suitability of the scales for different contexts is discussed. Many studies do not specifically set out to measure dementia-specific HRQL but do include related items. Determining how best to operationalize the many HRQL domains will be helpful for mapping measures of HRQL in such studies maximizing the value of existing resources.